非线性系统
积分器
控制理论(社会学)
缩放比例
严格反馈表
数学
班级(哲学)
转化(遗传学)
国家(计算机科学)
非线性控制
强迫(数学)
理论(学习稳定性)
计算机科学
自适应控制
反推
控制(管理)
物理
算法
人工智能
数学分析
量子力学
计算机网络
生物化学
化学
几何学
带宽(计算)
机器学习
基因
作者
P. Krishnamurthy,Farshad Khorrami,Miroslav Krstić
出处
期刊:Automatica
[Elsevier BV]
日期:2020-02-15
卷期号:115: 108860-108860
被引量:289
标识
DOI:10.1016/j.automatica.2020.108860
摘要
Abstract “Prescribed-time” stabilization addresses the problem of regulating the state to the origin in a fixed (prescribed) time irrespective of the initial state. While prior results on prescribed-time stabilization considered specific classes of systems such as a chain of integrators with uncertainties matched with the control input (i.e., normal form), we address here a general class of nonlinear systems in a generalized strict-feedback-like structure with state-dependent nonlinear uncertainties throughout the system dynamics. The proposed control design is based on our dynamic high gain scaling technique along with a novel temporal transformation and form of the scaling dynamics with temporal forcing terms. We show that the proposed control design achieves prescribed-time stabilization for the considered general class of uncertain nonlinear systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI